Basis of a real hermitian matrix vector space with complex entries

In summary, the conversation is about finding the dimension of a vector space, \mathrm{Herm}_n(\mathbb{C}), which consists of nxn Hermitian matrices. The attempt at a solution suggests that the dimension is 2n^2-n, but the paper states that it is n^2. It is then explained that this is because the entries on opposite sides of the diagonal are complex conjugates of each other, reducing the number of free choices. Ultimately, the dimension is determined to be n^2 when considering the vector space as a real vector space.
  • #1
_Andreas
144
1

Homework Statement



Let [tex]V[/tex] be the [tex]\mathbb{R}[/tex]-vector space [tex]\mbox{Herm}_n( \mathbb{C} )[/tex]. Find [tex]\dim_{\mathbb{R}} V[/tex].

The Attempt at a Solution



I'd say the dimension is [tex]2n(n-1)+n=2n^2-n[/tex], because all entries not on the main diagonal are complex, so you have [tex]n(n-1)[/tex] entries which you have to split up in two (the scalars are real), and n real entries on the main diagonal (which you don't have to split up in two). However, the paper I have says that [tex]\dim_{\mathbb{R}} V[/tex] is equal to [tex]n^2[/tex]. I can't see how that could be correct. Have I misunderstood something?
 
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  • #2
The entries on opposite sides of the diagonal also have to be complex conjugates of each other. So you can really only choose one side freely. I'd count that as 2*(n^2-n)/2+n.
 
  • #3
You can simply think of taking the nxn Hermitian matrices, and stacking its rows on top of one another. This "map" will allow you to identify [itex] \mathrm{Herm}_n(\mathbb{C}) [/itex] with [itex] \mathbb{C}^{n^2} [/itex] since the matrix will have n² elements. All of the basic rules for the vector space hold since we're only considering scalar multiplication and addition, which is done component-wise (note that this map only becomes tricky if you're considering [itex] \mathrm{Herm}_n(\mathbb{C}) [/itex] as an algebra, in which case you need to define your second binary operator in a special way). Thus you've reduced the question to, "what is the dimension of [itex] \mathbb{C}^{n^2} [/itex] when viewed as a real vector space?" Well this is just trivially n². Though it seems that they've ignored restrictions on the definition of a Hermitian matrix.
 
  • #4
Yeah, including the restrictions for Hermiticity, I would only count

[tex] \frac{1}{2} n^2 + \frac{1}{2} n [/tex]

Edit: I'm not too certain how you got [itex] 2n^2 - n [/itex] since in the unrestricted case (and hence upper bound) case we have n², but

for n>1, 2n²-n > n²
 
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  • #5
Much appreciated help. Thanks to both of you!
 

What is a real hermitian matrix vector space with complex entries?

A real hermitian matrix vector space with complex entries is a mathematical structure that consists of a set of vectors and a set of operations defined on those vectors. The vectors are represented by matrices with complex entries, and the operations are defined in a way that preserves the properties of a hermitian matrix, such as symmetry and positive definiteness.

What are the basis vectors of a real hermitian matrix vector space?

The basis vectors of a real hermitian matrix vector space are a set of linearly independent vectors that span the entire space. These vectors can be thought of as the building blocks of the space, and any vector in the space can be expressed as a linear combination of the basis vectors.

How is a real hermitian matrix vector space different from a real vector space?

A real hermitian matrix vector space is different from a real vector space in that it allows for complex entries in its matrices, while a real vector space only allows for real entries. This allows for more complex operations and transformations to be performed on the vectors in the space.

What are the applications of a real hermitian matrix vector space with complex entries?

A real hermitian matrix vector space with complex entries has many applications in the fields of quantum mechanics, signal processing, and data analysis. It is used to model and analyze complex systems, such as quantum systems and communication networks.

How is the basis of a real hermitian matrix vector space determined?

The basis of a real hermitian matrix vector space is determined by finding a set of linearly independent vectors that span the entire space. This can be done through various methods, such as Gaussian elimination or Gram-Schmidt orthogonalization.

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